The Challenge of Arbitrage in Crypto Markets
People get excited when they hear about arbitrage opportunities in the crypto market. That excitement is driven by frequently seeing big price differences between exchanges. If you have coding skills, you might think taking advantage of those price differences using arbitrage will be a piece of cake.
The real challenges come as you write, test, and run your code against exchange accounts. Here are just a few of the challenges that come from trying to execute an arbitrage strategy in the crypto market.
Most developers use simulations to verify their ideas and coding. However, depending on how you execute your simulation, your simulation results might be quite different from your real-world results. For example, if your simulation is based on the order book (open buy and sell orders), your simulation result might be totally misleading.
When you see price differences between exchanges, do you check price differences in the order book as well? Do you know if your orders will actually be fulfilled or the timing of those orders?
Capturing Future Opportunities
After you make some arbitrage transactions, you might find one exchange price is always higher than another. Opportunities to take advantage of arbitrage may decrease. How will you continue to profit with limited funds and fewer opportunities?
The crypto exchange is not like the stock exchange. Most crypto exchange APIs are not designed for high-frequency trading. Some APIs are poorly designed and unstable. The exchange may go down. The API server could stop responding. Perhaps internal logic or a limit is changed on the exchange side. There are many scenarios where API calls fail. It might be harder than you think to execute a robust arbitrage program without human interaction.
Weighing the Risks
Transaction fees are not cheap in crypto exchanges. If you have transaction success in one exchange, but failed transactions in another, you could lose money very quickly.
Of course, everyone would like to know if profit expectations through arbitrage are real and reliable. Many variables come into play when answering this question.
Choosing an Arbitrage Coding Strategy
In addition to two-point arbitrage, you also might hear about triangle or multiple-point arbitrage. Do you understand which strategy is best for you? Does fund size affect your arbitrage strategy? What is the proper fund size you should try? Answering these questions might be harder than you thought.
The parameters used by trading bots are also important. There is no “one size fits all” bot that can simply run for you all day every day. Bot parameters have to be set, tested, optimized, and then put into practice in the real world.
In this lab experiment, we conducted an arbitrage experiment to determine how to overcome the challenges mentioned above. This lab experiment will also verify what kind of data support is needed to maximize profit and minimize risk.
We ended the month with a profit of +0.81616874 BTC (+55.34%), and +80.02477571 LSK (+8.07%).
We see our transactions in the real world, fully automated, with a dynamic configuration of different variables and parameters.
This lab experiment was conducted on several combinations of currencies (such as: BTC/LSK, BTC/USD, BTC/IOTA, BTC/ETH) and on different exchanges.
All experiments were successful. In this Coinscious Lab experiment, we looked at the results of our BTC/LSK arbitrage. For data and information on other experiments, please contact us.
Based on different experiments completed by Coinscious Lab, the Coinscious product team will create new product designs that cover the various needs in crypto arbitrage. These designs will not only help traders capture more opportunities, but also will optimize the process through simulation, AI optimization, profit estimation, and so on.